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cs.AI2026
A Modular Agentic Framework for Synthetically Constrained Multi-Objective Hit-to-Lead Optimization
Kelvin P. Idanwekhai, Enes Kelestemur, Benjamin Strickland +6
Hit-to-lead optimization requires iterative design of hit analogs across competing potency, selectivity, physicochemical, pharmacokinetic, safety, and synthetic constraints. We pre…
cs.AI2017★ 1.2k cited
Deep Reinforcement Learning for De-Novo Drug Design
Mariya Popova, Olexandr Isayev, Alexander Tropsha
We propose a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcement Learning for Structural Evolution). Based on deep an…